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DESCRIPTION
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DESCRIPTION
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Package: evalITR
Title: Evaluating Individualized Treatment Rules
Version: 1.0.0
Date: 2023-08-20
Authors@R: c(
person("Michael Lingzhi", "Li", , "[email protected]", role = c("aut", "cre")),
person("Kosuke", "Imai", , "[email protected]", role = "aut"),
person("Jialu", "Li", , "[email protected]", role = "ctb"),
person("Xiaolong", "Yang", , "[email protected]", role = "ctb")
)
Maintainer: Michael Lingzhi Li <[email protected]>
Description: Provides various statistical methods for evaluating
Individualized Treatment Rules under randomized data. The provided
metrics include Population Average Value (PAV), Population Average
Prescription Effect (PAPE), Area Under Prescription Effect Curve
(AUPEC). It also provides the tools to analyze Individualized
Treatment Rules under budget constraints. Detailed reference in Imai
and Li (2019) <arXiv:1905.05389>.
License: GPL (>=2)
URL: https://github.com/MichaelLLi/evalITR,
https://michaellli.github.io/evalITR/,
https://jialul.github.io/causal-ml/
BugReports: https://github.com/MichaelLLi/evalITR/issues
Depends:
dplyr (>= 1.0),
MASS (>= 7.0),
Matrix (>= 1.0),
quadprog (>= 1.0),
R (>= 3.5.0),
stats
Imports:
caret,
cli,
e1071,
forcats,
gbm,
ggdist,
ggplot2,
ggthemes,
glmnet,
grf,
haven,
purrr,
rlang,
rpart,
rqPen,
scales,
utils,
bartCause,
SuperLearner
Suggests:
doParallel,
furrr,
knitr,
rmarkdown,
testthat,
bartMachine,
elasticnet,
randomForest,
spelling
VignetteBuilder:
knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.2
Language: en-US